Robust least square configuration and its application in structural health monitoring

With social and economic development, more and more high-rise buildings are constructed in cities. The structural health monitoring of tall buildings has become increasingly important and necessary. Traditional theories and methods of data processing are commonly used in regression curve and multiple linear regressions etc. But they only can be used for dealing with similar observations, on the other hand, the gross error of data has no good approach to analysis and calculate in high precise. In this paper, the, robust least squares collocation method is configured to deal with these two issues simultaneously. First of all, the function of least square configuration model and accuracy evaluation model are brought forward. Then we establish the robust subsequent configuration model, and the configuration model in the determination of covariance function method is analyzed. An applied project of robust least square configuration in a tall building health monitoring and the superiority also introduced.